| language: zh | |
| tags: | |
| - image-classification | |
| - handwriting | |
| - chinese | |
| - keras | |
| - tensorflow | |
| license: mit | |
| # Chinese Handwriting Recognition – HSK1 | |
| A CNN trained on the HWDB1.0 dataset to recognise **178 Chinese characters**. | |
| ## Model details | |
| | Item | Value | | |
| |---|---| | |
| | Input | 40×40 grayscale image | | |
| | Classes | 178 Chinese characters + Unknown | | |
| | Framework | Keras / TensorFlow | | |
| | Confidence threshold | 0.5 (below → Unknown) | | |
| ## Files | |
| | File | Description | | |
| |---|---| | |
| | `chinese_hsk1_model.keras` | Trained Keras model | | |
| | `label_map.json` | Index-to-character mapping | | |
| | `training_curves.png` | Accuracy & loss curves | | |
| ## Quick start | |
| ```python | |
| import numpy as np, json | |
| from tensorflow import keras | |
| model = keras.models.load_model('chinese_hsk1_model.keras') | |
| label_map = json.load(open('label_map.json', encoding='utf-8')) | |
| THRESHOLD = 0.5 | |
| def predict(img_40x40_gray): | |
| x = img_40x40_gray.astype('float32') / 255.0 | |
| x = x.reshape(1, 40, 40, 1) | |
| probs = model.predict(x)[0] | |
| conf = probs.max() | |
| if conf < THRESHOLD: | |
| return 'Unknown', conf | |
| return label_map[str(probs.argmax())], conf | |
| ``` | |